Security & IT News

Overview Rapid7 Labs recently identified a chain of security vulnerabilities in the Gainsight Assist plugin and its interactions with the associated domain app.gainsight.com . These vulnerabilities include an Information Disclosure flaw ( CVE-2026-31381 ) and a Reflected Cross-Site Scripting (XSS) vulnerability ( CVE-2026-31382 ). By chaining these vulnerabilities, an attacker can move from passive information gathering to active client-side exploitation. The XSS vulnerability was remediated by Gainsight via a server side code-level fix on March 6, 2026. A patched update to the Chrome and Outlook plugins to remediate the Information Disclosure were released on March 9, 2026. Product description Gainsight Assist is a plugin that allows users to access Gainsight email templates and easily sync inbound and outbound emails to the Timeline within the Gainsight Customer Success (CS) product directly from their email platform. Credit These vulnerabilities were discovered and reported to the Gainsight team by Christopher O’Boyle, Cybersecurity Advisor at Rapid7. The vulnerabilities are being disclosed in accordance with Rapid7's vulnerability disclosure policy . Rapid7 is grateful to the Gainsight team for their assistance and collaboration. Vulnerability details CVE Description CVSS CVE-2026-31381 Information Disclosure: An attacker can extract user email addresses (PII) exposed in base64 encoding via the state parameter in the OAuth callback URL. 5.3 (Medium) CVE-2026-31382 Reflected XSS / HTML Injection: The error_description parameter is vulnerable to Reflected XSS. An attacker can bypass the domain's WAF using a Safari-specific onpagereveal payload. 6.1 (Medium) The testing target was the Gainsight Assist plugin and its interactions with the app.gainsight.com domain, used as a callback mechanism that processes authentication data and error descriptions following user login attempts. CVE-2026-31381: Information disclosure During testing involving Salesforce and Okta authentication channels, an OAuth callback flow failure was observed. The resulting error message exposed the user's email address (PII) within a Base64 encoded state parameter in the URL. Because Base64 is merely obfuscation and not encryption, these email addresses can be easily harvested from server logs, proxies, or browser history by third parties. CVE-2026-31382: Reflected XSS and HTML injection The Gainsight callback URL contained an error_description parameter that was found to be vulnerable to content spoofing and HTML Injection. While Gainsight employs a Web Application Firewall (WAF) that successfully blocks most standard JavaScript execution, Rapid7 researchers bypassed this protection using a browser-specific payload targeting Safari’s onpagereveal event. When the victim opens the malicious URL in Safari, the onpagereveal payload executes automatically without further user interaction. By injecting HTML content and spoofing the error page, an attacker can create a legitimate-

p CISA and the Federal Bureau of Investigation released a a href= https://www.ic3.gov/PSA/2026/PSA260320 target= _blank Public Service Announcement (PSA) /a warning about ongoing phishing campaigns by cyber actors associated with the Russian Intelligence Services targeting commercial messaging applications (CMAs). These campaigns aim to bypass encryption to compromise to individual user accounts with targets including current and former U.S. government officials, military personnel, political figures, and journalists. nbsp; nbsp; /p p Evidence shows that cyber actors have been able to compromise individual CMA accounts, but not encryption of the applications themselves. The actors’ global campaigns have resulted in unauthorized access to thousands of individual CMA accounts to view the victims’ messages and contact lists, send messages, and conduct additional phishing against other CMA accounts. nbsp; /p p CISA and FBI urge CMA users to review the PSA, follow recommended cybersecurity practices, and remain vigilant for suspicious activity. /p

p CISA has added five new vulnerabilities to its a href="https://www.cisa.gov/known-exploited-vulnerabilities-catalog" data-entity-type="node" data-entity-uuid="79453b83-86b9-4e2f-b1ec-abf73c6eb291" data-entity-substitution="canonical" title="Known Exploited Vulnerabilities Catalog" Known Exploited Vulnerabilities (KEV) Catalog /a , based on evidence of active exploitation. /p ul li a href="https://www.cve.org/CVERecord?id=CVE-2025-31277" target="_blank" CVE-2025-31277 /a Apple Multiple Products Buffer Overflow Vulnerability /li li a href="https://www.cve.org/CVERecord?id=CVE-2025-32432" target="_blank" CVE-2025-32432 /a Craft CMS Code Injection Vulnerability /li li a href="https://www.cve.org/CVERecord?id=CVE-2025-43510" target="_blank" CVE-2025-43510 /a Apple Multiple Products Improper Locking Vulnerability /li li a href="https://www.cve.org/CVERecord?id=CVE-2025-43520" target="_blank" CVE-2025-43520 /a Apple Multiple Products Classic Buffer Overflow Vulnerability /li li a href="https://www.cve.org/CVERecord?id=CVE-2025-54068" target="_blank" CVE-2025-54068 /a Laravel Livewire Code Injection Vulnerability /li /ul p These types of vulnerabilities are frequent attack vectors for malicious cyber actors and pose significant risks to the federal enterprise. /p p a href="https://www.cisa.gov/binding-operational-directive-22-01" Binding Operational Directive (BOD) 22-01: Reducing the Significant Risk of Known Exploited Vulnerabilities /a established the KEV Catalog as a living list of known Common Vulnerabilities and Exposures (CVEs) that carry significant risk to the federal enterprise. BOD 22-01 requires Federal Civilian Executive Branch (FCEB) agencies to remediate identified vulnerabilities by the due date to protect FCEB networks against active threats. See the a href="https://www.cisa.gov/sites/default/files/publications/Reducing_the_Significant_Risk_of_Known_Exploited_Vulnerabilities_211103.pdf" BOD 22-01 Fact Sheet /a for more information. /p p Although BOD 22-01 only applies to FCEB agencies, CISA strongly urges all organizations to reduce their exposure to cyberattacks by prioritizing timely remediation of a href="https://www.cisa.gov/known-exploited-vulnerabilities-catalog" data-entity-type="node" data-entity-uuid="79453b83-86b9-4e2f-b1ec-abf73c6eb291" data-entity-substitution="canonical" title="Known Exploited Vulnerabilities Catalog" KEV Catalog vulnerabilities /a as part of their vulnerability management practice. CISA will continue to add vulnerabilities to the catalog that meet the a href="https://www.cisa.gov/known-exploited-vulnerabilities" data-entity-type="node" data-entity-uuid="f2adba9a-0404-494c-a90c-4363a4a5c934" data-entity-substitution="canonical" title="Reducing the Significant Risk of Known Exploited Vulnerabilities" specified criteria /a . nbsp; /p

404 Media has a story about Proton Mail giving subscriber data to the Swiss government, who passed the information to the FBI. It’s metadata—payment information related to a particular account—but still important knowledge. This sort of thing happens, even to privacy-centric companies like Proton Mail.

Yesterday, I discovered a malicious Bash script that installs a GSocket backdoor on the victim s computer. I don t know the source of the script not how it is delivered to the victim. GSocket[ 1 ] is a networking tool, but also a relay infrastructure, that enables direct, peer-to-peer style communication between systems using a shared secret instead of IP addresses or open ports. It works by having both sides connect outbound to a global relay network. Tools like gs-netcat can provide remote shells, file transfer, or tunneling and bypass classic security controls. The script that I found uses a copy of gs-netcat but the way it implements persistence and anti-forensic techniques deserves a review. A few weeks ago, I found a sample that used GSocket connectivity as a C2 channel. It makes me curious and I started to hunt for more samples. Bingo! The new one that I found (SHA256:6ce69f0a0db6c5e1479d2b05fb361846957f5ad8170f5e43c7d66928a43f3286[ 2 ]) has been detected by only 17 antivirus solutions on VT. The script is not obfuscated and even has comments so I think that it was uploaded on VT for testing purposes by the developper (just a guess) Let s have a look at the techniques used. When you execute it in a sandbox, you see this: Note the identification of the tool ( G-Socket Bypass Stealth ) and the reference to @bboscat [ 3 ] A GSocket client is downloaded, started and is talking to the following IP: The malware implements persistence through different well-known techniques on Linux. First, a cron job is created: Every top-hour, the disguised gs-netcat will be killed (if running) and restarted. To improve persistence, the same code is added to the victim's .profile: The malware itself is copied in .ssh/putty and the GSocket shared secret stored in a fake SSH key file: The ELF file id_rsa (SHA256: d94f75a70b5cabaf786ac57177ed841732e62bdcc9a29e06e5b41d9be567bcfa) is the gs-netcat tool downloaded directly from the G-Socket CDN. Ok, let s have a look at an interesting anti-forensic technique implemented in the Bash script. File operations are not simply performed using classic commands like cp, rm, mv, etc. They are embedded in helper functions with a timestamp tracking/restoration system so the malware can later hide filesystem changes. Here is an example with a function that will create a file: mk_file() { local fn local oldest local pdir local pdir_added fn= $1 local exists # DEBUGF ${CC}MK_FILE($fn)${CN} pdir= $(dirname $fn ) [[ -e $fn ]] exists=1 ts_is_marked $pdir || { # HERE: Parent not tracked _ts_add $pdir NOT BY XMKDIR pdir_added=1 } ts_is_marked $fn || { # HERE: Not yet tracked _ts_get_ts $fn # Do not add creation fails. touch $fn 2 /dev/null || { # HERE: Permission denied [[ -n $pdir_added ]] { # Remove pdir if it was added above # Bash 5.0 does not support arr[-1] # Quote ( ) to silence shellcheck unset _ts_ts_a[${#_ts_ts_a[@]}-1] unset _ts_fn_a[${#_ts_fn_a[@]}-1] unset _ts_mkdir_fn_a[${#_ts_mkdir_fn_a[@]}-1] } return 69 # False } [[

(c) SANS Internet Storm Center. https://isc.sans.edu Creative Commons Attribution-Noncommercial 3.0 United States License.

The U.S. Justice Department joined authorities in Canada and Germany in dismantling the online infrastructure behind four highly disruptive botnets that compromised more than three million Internet of Things (IoT) devices, such as routers and web cameras. The feds say the four botnets — named Aisuru , Kimwolf , JackSkid and Mossad — are responsible for a series of recent record-smashing distributed denial-of-service (DDoS) attacks capable of knocking nearly any target offline. Image: Shutterstock, @Elzicon. The Justice Department said the Department of Defense Office of Inspector General’s (DoDIG) Defense Criminal Investigative Service (DCIS) executed seizure warrants targeting multiple U.S.-registered domains, virtual servers, and other infrastructure involved in DDoS attacks against Internet addresses owned by the DoD. The government alleges the unnamed people in control of the four botnets used their crime machines to launch hundreds of thousands of DDoS attacks, often demanding extortion payments from victims. Some victims reported tens of thousands of dollars in losses and remediation expenses. The oldest of the botnets — Aisuru — issued more than 200,000 attacks commands, while JackSkid hurled at least 90,000 attacks. Kimwolf issued more than 25,000 attack commands, the government said, while Mossad was blamed for roughy 1,000 digital sieges. The DOJ said the law enforcement action was designed to prevent further infection to victim devices and to limit or eliminate the ability of the botnets to launch future attacks. The case is being investigated by the DCIS with help from the FBI’s field office in Anchorage, Alaska, and the DOJ’s statement credits nearly two dozen technology companies with assisting in the operation. “By working closely with DCIS and our international law enforcement partners, we collectively identified and disrupted criminal infrastructure used to carry out large-scale DDoS attacks,” said Special Agent in Charge Rebecca Day of the FBI Anchorage Field Office. Aisuru emerged in late 2024, and by mid-2025 it was launching record-breaking DDoS attacks as it rapidly infected new IoT devices. In October 2025, Aisuru was used to seed Kimwolf, an Aisuru variant which introduced a novel spreading mechanism that allowed the botnet to infect devices hidden behind the protection of the user’s internal network. On January 2, 2026, the security firm Synthient publicly disclosed the vulnerability Kimwolf was using to propagate so quickly. That disclosure helped curtail Kimwolf’s spread somewhat, but since then several other IoT botnets have emerged that effectively copy Kimwolf’s spreading methods while competing for the same pool of vulnerable devices. According to the DOJ, the JackSkid botnet also sought out systems on internal networks just like Kimwolf. The DOJ said its disruption of the four botnets coincided with “law enforcement actions” conducted in Canada and G

iPhone hacking techniques have sometimes been described almost like rare and elusive animals: Hackers have used them so stealthily and carefully against such a small number of hand-picked targets that they're only rarely seen in the wild. Now a recent spate of espionage and cybercriminal campaigns has instead deployed those same phone-takeover tools, embedded in infected websites, to indiscriminately hack phones by the thousands. And one new technique in particular—capable of taking over any of hundreds of millions of iOS devices —has appeared on the web in an easily reusable form, putting a significant fraction of the world's iPhone users at risk. Researchers at Google and cybersecurity firms iVerify and Lookout on Wednesday jointly revealed the discovery of a sophisticated iPhone hacking technique known as DarkSword that they've seen in use on infected websites, capable of instantly and silently hacking iOS devices that visit those sites. While the technique doesn't affect the latest updated versions of iOS, it does work against iOS devices running versions of Apple's previous operating system release, iOS 18, which as of last month still accounted for close to a quarter of iPhones, according to Apple's own count. “A vast number of iOS users could have all of their personal data stolen simply for visiting a popular website,” says Rocky Cole, iVerify's cofounder and CEO. “Hundreds of millions of people who are still using older Apple devices or older operating system versions remain vulnerable.” Read full article Comments

Over the past year, I have had conversations with security leaders across a variety of disciplines, and the energy around AI is undeniable. Organizations are moving fast, and security teams are rising to meet the moment. Time and again, the question comes back to the same thing: “We’re adopting AI fast, how do we make sure our security keeps pace?” Explore the updated Microsoft Zero Trust Workshop and Assessment It’s the right question, and it’s the one we’ve been working to answer by updating the tools and guidance you already rely on. We’re announcing Microsoft’s approach to Zero Trust for AI (ZT4AI). Zero Trust for AI extends proven Zero Trust principles to the full AI lifecycle—from data ingestion and model training to deployment and agent behavior. Today, we’re releasing a new set of tools and guidance to help you move forward with confidence: A new AI pillar in the Zero Trust Workshop . Updated Data and Networking pillars in the Zero Trust Assessment tool. A new Zero Trust reference architecture for AI. Practical patterns and practices for securing AI at scale. Here’s what’s new and how to use it. Why Zero Trust principles must extend to AI AI systems don’t fit neatly into traditional security models. They introduce new trust boundaries—between users and agents, models and data, and humans and automated decision-making. As organizations adopt autonomous and semi-autonomous AI agents, a new class of risk emerges: agents that are overprivileged, manipulated, or misaligned can act like “double agents,” working against the very outcomes they were built to support. Watch the video: AI with Zero Trust Security By applying three foundational principles of Zero Trust to AI: Verify explicitly —Continuously evaluate the identity and behavior of AI agents, workloads, and users. Apply least privilege —Restrict access to models, prompts, plugins, and data sources to only what’s needed. Assume breach —Design AI systems to be resilient to prompt injection, data poisoning, and lateral movement. These aren’t new principles. What’s new is how we apply them systematically to AI environments. A unified journey: Strategy → assessment → implementation The most common challenge we hear from security leaders and practitioners is a lack of a clear, structured path from knowing what to do to doing it. That’s what Microsoft’s approach to Zero Trust for AI is designed to solve—to help you get to next steps and actions, quickly. Zero Trust Workshop—now with an AI pillar Building on last year’s announcement , the Zero Trust Workshop has been updated with a dedicated AI pillar, now covering 700 security controls across 116 logical groups and 33 functional swim lanes. It is scenario-based and prescriptive, designed to move teams from assessment to execution with clarity and speed. The workshop helps organizations: Align security, IT, and business stakeholders on sha

Earlier this year, we made a significant announcement: Rapid7 partnered with ARMO to add AI-powered cloud application detection and response (CADR) – or cloud runtime security – to our cloud security portfolio. At the time, I published a blog highlighting this two-part approach for modern cloud security that combines preemptive exposure management (understanding the threats that could exist) with proactive runtime security (detecting the threats that are happening). Today, we are thrilled to announce that this vision is fully realized and integrated with Rapid7 Exposure Command . For our customers, this milestone represents our ability to deliver on the promise of a complete Cloud-Native Application Protection Platform (CNAPP) that helps security teams preemptively identify and proactively thwart attacks. Exploring the possibilities of this unified CNAPP At Rapid7, we believe that a CNAPP is unified if it operates from a single, objective source of truth. By integrating cloud runtime security directly into Exposure Command, we are seamlessly merging the preemptive (posture, configurations, identities, and vulnerabilities) with the proactive (runtime behavior and active threats). The table below summarizes this enhancement: ⠀ Today’s Rapid7 Cloud Security solution What cloud runtime adds Primary Focus Prevention, risk reduction, and preemptive response Real-time exposure detection and proactive response Core Question "What is vulnerable and could be attacked?" "Is an attacker exploiting our environment now?" Lifecycle Stage Pre-deployment, continuous scanning, or periodic intervals Continuous monitoring of live (in-production) workloads What It Finds Misconfigurations, exposed secrets, software CVEs, missing patches Active exploits, lateral movement, unauthorized process execution, SQL injection ⠀ The true power of this unified architecture is best understood through the lens of a security practitioner’s daily battle against cloud threats. The previous blog post discussed this in theory; let’s use this blog to talk about the reality. The baseline Exposure Command continuously scans and assesses your cloud posture to identify whether a container exposure exists in a production cluster. Traditional scanners would stop here, leaving you to prioritize this vulnerability against others. In Exposure Command, this detection is not just part of a static score, but instead it is part of an attack path. Our preemptive security platform tells you, for instance, whether this specific container has internet access and an over-privileged IAM role, making it highly reachable and exploitable. This means that you are not just looking at a CVE; you are looking at the potential blueprint behind a major breach. The proactive validation This is where cloud runtime security turns theory into reality. Instead of treating the vulnerability as just a potential risk, the platform utilizes eBPF sensors to provide continuous, direct kernel-level observability and application

In this article A wide range of tax-themed campaigns How to protect users and organization against tax-themed campaigns Microsoft Defender detection and hunting guidance Indicators of compromise During tax season, threat actors reliably take advantage of the urgency and familiarity of time-sensitive emails, including refund notices, payroll forms, filing reminders, and requests from tax professionals, to trick targets into opening malicious attachments, scanning QR codes, or following multi-step link chains. Every year, there is an observable uptick in tax-themed campaigns as Tax Day (April 15) approaches in the United States, and this year is no different. In recent months, Microsoft Threat Intelligence identified email campaigns using lures around W-2, tax forms, or similar themes, or posing as government tax agencies, tax services firms, and relevant financial institutions. Many campaigns target individuals for personal and financial data theft, but others specifically target accountants and other professionals who handle sensitive documents, have access to financial data, and are accustomed to receiving tax-related emails during this period. Identified campaigns were designed to harvest credentials or deliver malware. Phishing-as-a-service (PhaaS) platforms continue to be prevalent, enabling highly convincing credential theft and multifactor authentication (MFA) bypass campaigns through tailored tax-themed social engineering lures, attachments, and phishing pages. In cases of malware delivery, we noted a continued trend of abusing legitimate remote monitoring and management tools (RMMs), which allow threat actors to maintain persistence on a compromised device or network, enable an alternative command-and-control method, or, in the case of hands-on-keyboard attacks, use as an interactive remote desktop session. INSIDE TYCOON 2FA How a leading AiTM phishing kit operated at scale › This blog details several of the campaigns observed by Microsoft Threat Intelligence in the past few months that leveraged the tax season for social engineering. By educating users about phishing lures, configuring essential email security settings, and defending against credential theft, individuals and organizations can defend against both this seasonal surge in phishing attacks and more broadly against many types of phishing attacks that we observe. A wide range of tax-themed campaigns CPA lures leading to Energy365 phishing kit In early February 2026, we observed a campaign that was delivering the Energy365 PhaaS phishing kit and used tax and Certified Public Accountant (CPA) lures throughout the attack chain. This campaign stood out due to its highly specific lure customization, in contrast to other threat actors who use this popular phishing kit but employ generic lures. Other notable characteristics of this campaign include the involvement of multiple file formats such as Excel and OneNote, use of legitimate infrastructure such as OneDrive, and multiple rounds

p a href= https://github.com/cisagov/CSAF/blob/develop/csaf_files/OT/white/2026/icsa-26-078-08.json strong View CSAF /strong /a /p h2 Summary /h2 p strong Successful exploitation of these vulnerabilities could allow an attacker to read, intercept, or modify communications. /strong /p p The following versions of Automated Logic WebCTRL Premium Server are affected: /p ul li WebCTRL Premium Server /li /ul div class= csaf-table table class= tablesaw tablesaw-stack data-tablesaw-mode= stack data-tablesaw-minimap thead tr th role= columnheader data-tablesaw-priority= persist CVSS /th th role= columnheader Vendor /th th role= columnheader Equipment /th th role= columnheader Vulnerabilities /th /tr /thead tbody tr td v3 9.1 /td td Automated Logic /td td Automated Logic WebCTRL Premium Server /td td Multiple Binds to the Same Port, Authentication Bypass by Spoofing, Cleartext Transmission of Sensitive Information /td /tr /tbody /table /div h3 Background /h3 ul li strong Critical Infrastructure Sectors: /strong Commercial Facilities /li li strong Countries/Areas Deployed: /strong Worldwide /li li strong Company Headquarters Location: /strong United States /li /ul hr h2 Vulnerabilities /h2 div class= csaf-accordion p a class= csaf-accordion-toggle-all href= # Expand All + /a /p div class= csaf-accordion-item h3 a class= csaf-accordion-toggle href= # CVE-2026-25086 /a /h3 div class= csaf-accordion-content p Under certain conditions, an attacker could bind to the same port used by WebCTRL. This could allow the attacker to craft and send malicious packets and impersonate the WebCTRL service without requiring code injection into the WebCTRL software. /p p a href= https://www.cve.org/CVERecord?id=CVE-2026-25086 View CVE Details /a /p hr h4 Affected Products /h4 h5 Automated Logic WebCTRL Premium Server /h5 div class= ics-vendor-version-status div class= ics-vendor strong Vendor: /strong br Automated Logic /div div class= ics-version strong Product Version: /strong br Automated Logic WebCTRL Premium Server: lt;v8.5 /div div class= ics-status strong Product Status: /strong br known_affected /div /div div class= ics-remediations h6 Remediations /h6 p strong Mitigation /strong br Automated Logic notes that WebCTRL 7 is End of Life (EOL) and has been out of support since January 27, 2023. Users are advised to upgrade to the latest version of the WebCTRL server application, which supports the more secure BACnet/SC. /p p strong Mitigation /strong br For customers using supported versions of WebCTRL (WebCTRL 8.5 cumulative releases and later), Automated Logic provides secure configuration guidance for hardware and software deployments; BACnet Secure Connect (BACnet/SC) support, which introduces TLS encryption and mutual authentication; and published best practices for network segmentation, access control, and secure protocol implementation. Additional information is available at: https://www.automatedlogic.com/en/company/security-commitment/. br a href= https://www.auto

p a href= https://github.com/cisagov/CSAF/blob/develop/csaf_files/OT/white/2026/icsa-26-078-02.json strong View CSAF /strong /a /p h2 Summary /h2 p strong Successful exploitation of this vulnerability may risk a Cross-site Scripting or an open redirect attack which could result in an account takeover scenario or the execution of code in the user browser. /strong /p p The following versions of Schneider Electric Modicon Controllers M241, M251, M258, and LMC058 are affected: /p ul li Modicon M241 versions prior to 5.4.13.12 Modicon_Controller_M241 /li li Modicon M251 versions prior to 5.4.13.12 Modicon_Controller_M251 /li li Modicon Controllers M258 all firmware versions Modicon_Controllers_M258 /li li Modicon Controllers LMC058 all firmware versions Modicon_Controllers_LMC058 /li /ul div class= csaf-table table class= tablesaw tablesaw-stack data-tablesaw-mode= stack data-tablesaw-minimap thead tr th role= columnheader data-tablesaw-priority= persist CVSS /th th role= columnheader Vendor /th th role= columnheader Equipment /th th role= columnheader Vulnerabilities /th /tr /thead tbody tr td v3 5.4 /td td Schneider Electric /td td Schneider Electric Modicon Controllers M241, M251, M258, and LMC058 /td td Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting') /td /tr /tbody /table /div h3 Background /h3 ul li strong Critical Infrastructure Sectors: /strong Commercial Facilities, Critical Manufacturing, Energy /li li strong Countries/Areas Deployed: /strong Worldwide /li li strong Company Headquarters Location: /strong France /li /ul hr h2 Vulnerabilities /h2 div class= csaf-accordion p a class= csaf-accordion-toggle-all href= # Expand All + /a /p div class= csaf-accordion-item h3 a class= csaf-accordion-toggle href= # CVE-2025-13902 /a /h3 div class= csaf-accordion-content p CWE-79 Improper Neutralization of Input During Web Page Generation ('Cross-site Scripting') vulnerability exists that could cause condition where authenticated attackers can have a victim's browser run arbitrary JavaScript when the victim hovers over a maliciously crafted element on a web server containing the injected payload. /p p a href= https://www.cve.org/CVERecord?id=CVE-2025-13902 View CVE Details /a /p hr h4 Affected Products /h4 h5 Schneider Electric Modicon Controllers M241, M251, M258, and LMC058 /h5 div class= ics-vendor-version-status div class= ics-vendor strong Vendor: /strong br Schneider Electric /div div class= ics-version strong Product Version: /strong br Schneider Electric Modicon M241 versions prior to 5.4.13.12: Modicon_Controller_M241, Schneider Electric Modicon M251 versions prior to 5.4.13.12: Modicon_Controller_M251, Schneider Electric Modicon Controllers M258 all firmware versions: Modicon_Controllers_M258, Schneider Electric Modicon Controllers LMC058 all firmware versions: Modicon_Controllers_LMC058 /div div class= ics-status strong Product Status: /strong br known_affected /div /div div class=

p a href= https://github.com/cisagov/CSAF/blob/develop/csaf_files/OT/white/2026/icsa-26-078-06.json strong View CSAF /strong /a /p h2 Summary /h2 p strong Successful exploitation of these vulnerabilities could enable attackers to gain unauthorized administrative control over vulnerable charging stations or disrupt charging services through denial-of-service attacks. /strong /p p The following versions of CTEK Chargeportal are affected: /p ul li Chargeportal vers:all/* /li /ul div class= csaf-table table class= tablesaw tablesaw-stack data-tablesaw-mode= stack data-tablesaw-minimap thead tr th role= columnheader data-tablesaw-priority= persist CVSS /th th role= columnheader Vendor /th th role= columnheader Equipment /th th role= columnheader Vulnerabilities /th /tr /thead tbody tr td v3 9.4 /td td CTEK /td td CTEK Chargeportal /td td Missing Authentication for Critical Function, Improper Restriction of Excessive Authentication Attempts, Insufficient Session Expiration, Insufficiently Protected Credentials /td /tr /tbody /table /div h3 Background /h3 ul li strong Critical Infrastructure Sectors: /strong Energy, Transportation Systems /li li strong Countries/Areas Deployed: /strong Worldwide /li li strong Company Headquarters Location: /strong Sweden /li /ul hr h2 Vulnerabilities /h2 div class= csaf-accordion p a class= csaf-accordion-toggle-all href= # Expand All + /a /p div class= csaf-accordion-item h3 a class= csaf-accordion-toggle href= # CVE-2026-25192 /a /h3 div class= csaf-accordion-content p WebSocket endpoints lack proper authentication mechanisms, enabling attackers to perform unauthorized station impersonation and manipulate data sent to the backend. An unauthenticated attacker can connect to the OCPP WebSocket endpoint using a known or discovered charging station identifier, then issue or receive OCPP commands as a legitimate charger. Given that no authentication is required, this can lead to privilege escalation, unauthorized control of charging infrastructure, and corruption of charging network data reported to the backend. /p p a href= https://www.cve.org/CVERecord?id=CVE-2026-25192 View CVE Details /a /p hr h4 Affected Products /h4 h5 CTEK Chargeportal /h5 div class= ics-vendor-version-status div class= ics-vendor strong Vendor: /strong br CTEK /div div class= ics-version strong Product Version: /strong br CTEK Chargeportal: vers:all/* /div div class= ics-status strong Product Status: /strong br known_affected /div /div div class= ics-remediations h6 Remediations /h6 p strong Mitigation /strong br CTEK will be sunsetting this product in April 2026. Please contact CTEK for more information https://www.ctek.com/support. br a href= https://www.ctek.com/support https://www.ctek.com/support /a /p /div p strong Relevant CWE: /strong a href= https://cwe.mitre.org/data/definitions/306.html CWE-306 Missing Authentication for Critical Function /a /p hr h4 Metrics /h4 div class= csaf-table csaf-metrics-table table class= tablesaw tablesaw-stac

p a href= https://github.com/cisagov/CSAF/blob/develop/csaf_files/OT/white/2026/icsa-26-078-07.json strong View CSAF /strong /a /p h2 Summary /h2 p strong Successful exploitation of these vulnerabilities could enable attackers to gain unauthorized administrative control over vulnerable charging stations or disrupt charging services through denial-of-service attacks. /strong /p p The following versions of IGL-Technologies eParking.fi are affected: /p ul li eParking.fi vers:all/* /li /ul div class= csaf-table table class= tablesaw tablesaw-stack data-tablesaw-mode= stack data-tablesaw-minimap thead tr th role= columnheader data-tablesaw-priority= persist CVSS /th th role= columnheader Vendor /th th role= columnheader Equipment /th th role= columnheader Vulnerabilities /th /tr /thead tbody tr td v3 9.4 /td td IGL-Technologies /td td IGL-Technologies eParking.fi /td td Missing Authentication for Critical Function, Improper Restriction of Excessive Authentication Attempts, Insufficient Session Expiration, Insufficiently Protected Credentials /td /tr /tbody /table /div h3 Background /h3 ul li strong Critical Infrastructure Sectors: /strong Energy, Transportation Systems /li li strong Countries/Areas Deployed: /strong Worldwide /li li strong Company Headquarters Location: /strong Finland /li /ul hr h2 Vulnerabilities /h2 div class= csaf-accordion p a class= csaf-accordion-toggle-all href= # Expand All + /a /p div class= csaf-accordion-item h3 a class= csaf-accordion-toggle href= # CVE-2026-29796 /a /h3 div class= csaf-accordion-content p WebSocket endpoints lack proper authentication mechanisms, enabling attackers to perform unauthorized station impersonation and manipulate data sent to the backend. An unauthenticated attacker can connect to the OCPP WebSocket endpoint using a known or discovered charging station identifier, then issue or receive OCPP commands as a legitimate charger. Given that no authentication is required, this can lead to privilege escalation, unauthorized control of charging infrastructure, and corruption of charging network data reported to the backend. /p p a href= https://www.cve.org/CVERecord?id=CVE-2026-29796 View CVE Details /a /p hr h4 Affected Products /h4 h5 IGL-Technologies eParking.fi /h5 div class= ics-vendor-version-status div class= ics-vendor strong Vendor: /strong br IGL-Technologies /div div class= ics-version strong Product Version: /strong br IGL-Technologies eParking.fi: vers:all/* /div div class= ics-status strong Product Status: /strong br known_affected /div /div div class= ics-remediations h6 Remediations /h6 p strong Mitigation /strong br IGL-Technologies has updated eParking's OCPP servers to reduce the risks posed by the vulnerability. These updates implemented the following security controls: br 1) Enforce modern security profiles and stronger authentication. br 2) Device‑level whitelisting was implemented to ensure that only authorized charging units can connect. br 3) Rate‑limiting controls preven

p a href= https://github.com/cisagov/CSAF/blob/develop/csaf_files/OT/white/2026/icsa-26-078-05.json strong View CSAF /strong /a /p h2 Summary /h2 p strong Successful exploitation of this vulnerability could allow a remote attacker to cause an out-of-bounds read, resulting in a denial-of-service condition in the affected products. /strong /p p The following versions of Mitsubishi Electric CNC Series are affected: /p ul li M800VW (BND-2051W000) lt;=BB /li li M800VS (BND-2052W000) lt;=BB /li li M80V (BND-2053W000) lt;=BB /li li M80VW (BND-2054W000) lt;=BB /li li M800W (BND-2005W000) lt;=FM /li li M800S (BND-2006W000) lt;=FM /li li M80 (BND-2007W000) lt;=FM /li li M80W (BND-2008W000) lt;=FM /li li E80 (BND-2009W000) lt;=FM /li li C80 (BND-2036W000) vers:all/* /li li M750VW (BND-1015W002) vers:all/* /li li M730VW (BND-1015W000) vers:all/* /li li M720VW (BND-1015W000) vers:all/* /li li M750VS (BND-1012W002) vers:all/* /li li M730VS (BND-1012W000-**) vers:all/* /li li M720VS (BND-1012W000) vers:all/* /li li M70V (BND-1018W000) vers:all/* /li li E70 (BND-1022W000) vers:all/* /li li NC Trainer2 (BND-1802W000) vers:all/* /li li NC Trainer2 plus (BND-1803W000) vers:all/* /li /ul div class= csaf-table table class= tablesaw tablesaw-stack data-tablesaw-mode= stack data-tablesaw-minimap thead tr th role= columnheader data-tablesaw-priority= persist CVSS /th th role= columnheader Vendor /th th role= columnheader Equipment /th th role= columnheader Vulnerabilities /th /tr /thead tbody tr td v3 5.9 /td td Mitsubishi Electric /td td Mitsubishi Electric CNC Series /td td Improper Validation of Specified Index, Position, or Offset in Input /td /tr /tbody /table /div h3 Background /h3 ul li strong Critical Infrastructure Sectors: /strong Critical Manufacturing /li li strong Countries/Areas Deployed: /strong Worldwide /li li strong Company Headquarters Location: /strong Japan /li /ul hr h2 Vulnerabilities /h2 div class= csaf-accordion p a class= csaf-accordion-toggle-all href= # Expand All + /a /p div class= csaf-accordion-item h3 a class= csaf-accordion-toggle href= # CVE-2025-2399 /a /h3 div class= csaf-accordion-content p Improper Validation of Specified Index, Position, or Offset in Input (CWE-1285) vulnerability in the affected products allows a remote attacker to cause an out-of-bounds read, resulting in a denial-of-service condition in the affected products by sending specially crafted packets to TCP port 683. /p p a href= https://www.cve.org/CVERecord?id=CVE-2025-2399 View CVE Details /a /p hr h4 Affected Products /h4 h5 Mitsubishi Electric CNC Series /h5 div class= ics-vendor-version-status div class= ics-vendor strong Vendor: /strong br Mitsubishi Electric /div div class= ics-version strong Product Version: /strong br Mitsubishi Electric M800VW (BND-2051W000): lt;=BB, Mitsubishi Electric M800VS (BND-2052W000): lt;=BB, Mitsubishi Electric M80V (BND-2053W000): lt;=BB, Mitsubishi Electric M80VW (BND-2054W000): lt;=BB, Mitsubishi Electric M800W (BND-2005W000): l

Someone tries to remote control his own DJI Romo vacuum, and ends up controlling 7,000 of them from all around the world. The IoT is horribly insecure, but we already knew that .

Adoption of Generative AI (GenAI) and agentic AI has accelerated from experimentation into real enterprise deployments. What began with copilots and chat interfaces has quickly evolved into powerful business systems that autonomously interact with sensitive data, call external APIs, connect to consequential tools, initiate workflows, and collaborate with other agents across enterprise environments. As these AI systems become core infrastructure, establishing clear, continuous visibility into how these systems behave in production can help teams detect risk, validate policy adherence, and maintain operational control. Observability is one of the foundational security and governance requirements for AI systems operating in production. Yet many organizations don’t understand the critical importance of observability for AI systems or how to implement effective AI observability. That mismatch creates potential blind spots at precisely the moment when visibility matters most. In February, Microsoft Corporate Vice President and Deputy Chief Information Security Officer, Yonatan Zunger, blogged about expanding Microsoft’s Secure Development Lifecycle (SDL) to address AI-specific security concerns. Today, we continue the discussion with a deep dive into observability as a necessity for the secure development of GenAI and agentic AI systems. For additional context, read the Secure Agentic AI for Your Frontier Transformation blog that covers how to manage agent sprawl, strengthen identity controls, and improve governance across your tenant. Observability for AI systems In traditional software, client apps make structured API calls and backend services execute predefined logic. Because code paths follow deterministic flows, traditional observability tools can surface straightforward metrics like latency, errors, and throughput to track software performance in production. GenAI and agentic AI systems complicate this model. AI systems are probabilistic by design and make complex decisions about what to do next as they run. This makes relying on predictable finite sets of success and failure modes much more difficult. We need to evolve the types of signals and telemetry collected so that we can accurately understand and govern what is happening in an AI system. Consider this scenario: an email agent asks a research agent to look up something on the web. The research agent fetches a page containing hidden instructions and passes the poisoned content back to the email agent as trusted input. The email agent, now operating under attacker influence, forwards sensitive documents to unauthorized recipients, resulting in data exfiltration. In this example, traditional health metrics stay green: no failures, no errors, no alerts. The system is working exactly as designed… except a boundary between untrusted external content and trusted agent context has been compromised. This illustrates how AI systems require a unique approach to observability. Without insights

The predictive window has collapsed. In 2025, high-impact vulnerabilities weren’t quietly accumulating risk. They were operationalized, and often within days. Today, Rapid7 Labs released the 2026 Global Threat Landscape Report , an in-depth analysis of how attacker behavior is evolving across vulnerability exploitation, ransomware operations, identity abuse, and AI-driven tradecraft. The data shows a clear pattern: exposure is being identified and weaponized faster than most organizations are set up to defend. From disclosure to exploitation in days, not weeks In 2025, confirmed exploitation of newly disclosed CVSS 7–10 vulnerabilities increased 105% year over year, rising from 71 to 146. The median time from publication to inclusion in CISA’s Known Exploited Vulnerabilities list fell from 8.5 days to 5.0 days. At the same time, the number of high-probability vulnerabilities that remained unexploited dropped sharply. The buffer that once allowed teams to triage and schedule remediation is shrinking to the point where some severe flaws were seen to have been exploited almost immediately. The broader trend is unmistakable: vulnerability management programs built around reactive remediation cycles are struggling to keep pace with adversaries operating at machine speed. Cybercrime as a structured market Cybercrime in 2025 no longer resembles chaotic hacking. It resembles platform capitalism. The report highlights how the underground economy now mirrors legitimate SaaS ecosystems. Initial Access Brokers obtain and validate network footholds. Ransomware operators focus on encryption and extortion. Infostealer operators sell subscription-style access to fresh credential logs. This specialization lowers barriers to entry and increases scale creating a supply chain in which access is acquired, packaged, priced, and sold to anyone who wants it. Ransomware is a good example of this business maturity. It was present in 42% of Rapid7 MDR investigations in 2025 with leak posts increasing 46.4% year over year, and the number of active groups growing from 102 to 140. That kind of growth is anything but random or coincidental: it is an indication of systemic changes to the ransomware ecosystem indicating growing sophistication, specialization, and, ultimately, risk. Logging in, not breaking in Authentication-based attacks remain incredibly common as the lack of consistency across organizations can lead to easy exploitation. Valid accounts without multi-factor authentication (MFA) were responsible for 43.9% of incidents over that year. Rather than forcing their way past defenses, attackers increasingly authenticate with stolen credentials, hijacked sessions, or abused tokens. This is where the increase in AI-driven attacks is particularly acute with the benefits generative AI can play in improving the maturity and sophistication of social engineering attacks. As enterprises extend trust across cloud platforms, SaaS ecosystems, APIs, and remote work environments, a

Surprising no one, Meta’s new AI glasses are a privacy disaster . I’m not sure what can be done here. This is a technology that will exist, whether we like it or not. Meanwhile, there is a new Android app that detects when there are smart glasses nearby.